1. Field of the Invention:
This invention relates to an image-processing system employing coring techniques for reducing the noise component of an image-representing signal, such as a television video signal. More particularly, this invention relates to such a system which reduces this noise component without introducing any significant amount of aliasing or other spurious spatial frequency components into the image-representing signal.
2. Description of the Prior Art:
Coring is a well known technique for reducing the noise component of an image-representing signal. Coring consists of selectively passing only those portions of the image-representing signal which have an absolute amplitude level exceeding a selected threshold magnitude. Coring is a non-linear process that inherently introduces spurious harmonic and intermodulation spatial frequency components into the image-representing signal. The relative power of these spurious spatial frequency components increase as the selected threshold magnitude increases. Therefore, the selection of the coring threshold magnitude is a tradeoff between that which is high enough to substantially reduce the noise component and yet is not so high as to introduce an intolerable amount of spurious spatial frequency components.
The noticeability of a noise component, to an observer of a displayed image derived from an image-representing signal, depends on both (1) the spatial frequency spectrum of the noise component relative to the spatial frequency spectrum of the signal component of the displayed image and (2) on the operation of the human visual system in perceiving noise.
It has been found that human visual system appears to compute a primitive spatial-frequency decomposition of luminous images, by partitioning spatial frequency information into a number of contiguous, overlapping spatial-frequency bands. Each band is roughly an octave wide and the center frequency of each band differs from its neighbors by roughly a factor of two. Research suggests that there are approximately seven bands or "channels" that span the 0.5 to 60 cycle/degree spatial-frequency range of the human visual system. The importance of these findings is that spatial frequency information more than a factor of two away from other spatial frequency information will be independently processed by the human visual system. It has been further found that the spatial-frequency processing that occurs in the human visual system is localized in space. Thus, the signals within each spatial-frequency channel are computed over small subregions of the image. These subregions overlap each other and are roughly two cycles wide at a particular frequency. If a sine wave grating image is employed as a test pattern, it is found that the threshold contrast-sensitivity function for the sine wave grating image rolls-off rapidly as the spatial frequency of the sine wave grating image is increased. That is, high spatial frequencies require high contrast to be seen (.perspectiveto.20% at 30 cycle/degree) but lower spatial frequencies require relatively low contrast to be seen (.perspectiveto.0.2% at 3 cycle/degree). It has been found that the ability of the human visual system to detect a change in the contrast of a sine wave grating image that is above threshold also is better at lower spatial frequencies than at higher spatial frequencies. Specifically, an average human subject, in order to correctly discriminate a changing contrast 75% of the time, requires roughly a 12% change in contrast for a 3 cycle/degree sine wave grating, but requires a 30% change in contrast for a 30 cycle/degree grating.
Based on the operation of the human visual system, it becomes clear that a relatively high signal-to-noise (S/N) ratio within an octave spatial frequency band tends to mask the noise (i.e. the noise becomes unnoticeable to an observer) and that this masking effect is more effective for a higher spatial frequency octave than it is for a lower spatial frequency octave. This is true because of the relative decrease in both contrast sensitivity and change-in-contrast sensitivity of the human visual system at higher spatial frequencies. On the other hand, a relatively small high spatial frequency noise component superimposed on a nearly uniform background, which is comprised of dc (zero) or very low spatial frequency video components, is easily noticed by the human visual system. This is significant because real-world images, for the most part, have a spatial frequency spectrum in two dimensions which contains a large amount of relatively low spatial frequency signal energy and only a small amount of high frequency signal energy. This makes any high spatial frequency noise particularly noticeable.
If only a single coring means is employed to core the entire spatial frequency spectrum of an input image-representing signal, the selected threshold magnitude is likely to be too small to satisfactorily reduce the noticeable noise component in one or more octave portions of this spatial frequency spectrum, while at the same time being so high in one or more other octave portions of this spatial frequency spectrum that an intolerable amount of spurious spatial-frequency component artifact is introduced in the displayed image.
This problem can be avoided by first spectrum analyzing the input image-representing signal into a plurality of contiguous subspectra bands, then separately coring each of these bands with a different appropriate selected threshold magnitude, and finally synthesizing these cored bands into a single output image-representing signal which is employed to derive the displayed image.
Reference is made to U.S. Pat. No. 4,442,454, which issued Apr. 10, 1984 to Powell, and is entitled "Image Processing Method Using a Block Overlap Transformation Procedure." This Powell patent discloses a spectrum analyzer for separating the spatial frequency spectrum of an applied sampled two-dimensional image-manifesting signal input into three contiguous subspectra. The spectrum analyzer disclosed in Powell includes predetermined direct transform networks for deriving a fine-detailed (relatively high spatial frequency) subspectrum output at the sampling density of the input signal, an intermediate detail (relatively intermediate spatial frequency) subspectrum output at a reduced sampling density, and a coarse detail (relatively low spatial frequency) subspectrum output at a further reduced sampling density. Each of the respective subspectra output signals from the analyzer is individually first cored and then operated on by an inverse transform network. An expand/interpolation filter is used to increase the sampling density of each of the coarse-detail and intermediate-detail subspectra back to the sampling density of the fine-detail subspectrum, after which the respective cored subspectra signals are summed to derive an output image-representing signal used to provide a reduced-noise display of the represented image.
Powell is aware that image processing of image-representing signals, for the purpose of reducing noise, tends to result in some distortion of local image values (i.e. an artifact of the processing itself is generated that is noticeable in the display of the processed image). In fact, the block overlap transformation procedure of Powell is intended to prevent a noticeable boundary from existing between adjacent blocks in the displayed image. These boundaries are undesirable because they lead to a checkerboard appearance in the displayed image that is unacceptable for high quality image reproduction. Powell also realizes that some distortion of local image values necessarily results from the non-linear coring process, and that this produces an artifact that noticeably affects both the displayed image signal and the residue of unwanted noise. Nevertheless, Powell believes that such an artifact of the coring process has to be tolerated in order to realize the desired noise reduction.